Intern-S2-Preview: Scientific Agentic Foundation Model
Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sustain progress across long task horizons. We present Intern-S2-Preview, a series of scientific agentic foundation models designed to support multimodal scientific understanding, reasoning, generation, and long-horizon tasks. The training pipeline begins with scientific multimodal pre-training over rendered scientific documents, interleaved image-text data, and diverse scientific corpora. Starting from the pretrained c
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- FuzzyOverlapping authors or contributors · 62%Kong/kong →
“Shared author/contributor keys: kong”
- FuzzyOverlapping authors or contributors · 62%keras-team/keras →
“Shared author/contributor keys: jin”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%google-research/google-research →
“Shared author/contributor keys: sun”
- FuzzyOverlapping authors or contributors · 62%langchain-ai/langchain →
“Shared author/contributor keys: gan”
- LinkedLinked via arxiv author · 85%Lei Bai →
“Intern-S2-Preview: Scientific Agentic Foundation Model”
- LinkedLinked via arxiv author · 85%Jiaqi Cao →
“Intern-S2-Preview: Scientific Agentic Foundation Model”
- LinkedLinked via arxiv author · 85%Chiyu Chen →
“Intern-S2-Preview: Scientific Agentic Foundation Model”
